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Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning algorithms implementation in the recurrent stroke prediction models. This research aims to investigate and compare the performance of machine learning algorithms using recurrent stroke clinical public datasets. In this study, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Bayesian Rule List (BRL) are used and compared their performance in the domain of recurrent stroke prediction model. The result of the empirical experiments shows that ANN scores the highest accuracy at 80.00%, follows by BRL with 75.91% and SVM with 60.45%.

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Publication Date
Mon Dec 01 2025
Journal Name
Results In Engineering
Kernel-based machine learning intrusion detection systems for ICMPv6 DDoS detection
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Publication Date
Thu Jun 30 2022
Journal Name
Gsc Biological And Pharmaceutical Sciences
Revision of public health and clinical importance of amoebiasis in Iraq
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Amebiasis, related to the pathogenic parasite Entamoeba histolytica, is a prominent cause of diarrhea globally. Amebiasis is primarily a disease of impoverished communities in developing nations, although it has recently arisen as a significant infection among returning tourists and immigrants. Severe cases are linked to a high case fatality rate. Although polymerase chain reaction (PCR)-based diagnosis is becoming more widely available, it is still underutilized. Treatment with nitroimidazoles is now suggested, however novel parasite medication research is a top priority. To avoid problems, amebiasis should be considered before corticosteroid therapy. Because there is no effective vaccination, sanitation and availability to clean w

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Publication Date
Thu Jun 30 2022
Journal Name
Gsc Biological And Pharmaceutical Sciences
Revision of public health and clinical importance of amoebiasis in Iraq
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Amebiasis, related to the pathogenic parasite Entamoeba histolytica, is a prominent cause of diarrhea globally. Amebiasis is primarily a disease of impoverished communities in developing nations, although it has recently arisen as a significant infection among returning tourists and immigrants. Severe cases are linked to a high case fatality rate. Although polymerase chain reaction (PCR)-based diagnosis is becoming more widely available, it is still underutilized. Treatment with nitroimidazoles is now suggested, however novel parasite medication research is a top priority. To avoid problems, amebiasis should be considered before corticosteroid therapy. Because there is no effective vaccination, sanitation and availability to clean w

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
A Cryptosystem for Database Security Based on TSFS Algorithm
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Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

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Publication Date
Sun Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Using the Generative Learning Model on the Achievement of First-Grade Intermediate Students of Chemical Concepts in Science
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Abstract

The current research aims to identify the effect of using a model of generative learning in the achievement of first-middle students of chemical concepts in science. The researcher adopted the null hypothesis, which is there is no statistically significant difference at the level (0.05) between the mean scores of the experimental group who study using the generative learning model and the average scores of the control group who study using the traditional method in the chemical concepts achievement test. The research consisted of (200) students of the first intermediate at Al-Farqadin Intermediate School for Boys affiliated with the Directorate of General Education in Baghdad Governorate / Al-Karkh 3 wit

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Administrative competencies in many of Iraqi public Organizations: comparative study.
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Competencies topic in general , and Administrative competencies in specific, are considered as important subject in the contemporary administrative literature in all countries as well as in public and privet Organizations. For this reason, we have need to study those competencies in many Iraqi Organizations.

Two Organizations wer chosen for this research one of them is the Institution of taxation, and the other is the General company of Electric the data and information related to the research have been collected by desined questioner which has been given to a sample of (50) persions divided eqully between the two maintioned organizations.

The results of the study had differences

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Evaluation of the Construction, Build, Operate and Transfer (B.O.T): Applied Research in Southern Cement State Company
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   Form of investment in infrastructure important factor to drive economic growth in any country, with the dwindling ability of governments to provide the necessary funds for such investments, emerged as a rising trend for private sector involvement in public projects and infrastructure, and one of these trends is the build-operate-transfer system (BOT), which commonly used in various developed and developing countries as one of the tools used in the implementation of these investments, as the private sector under this system design, finance, build and operate the project, and are re-administration of the state after a certain period under a contractual agreement between the parties of the contract. As this system provides majo

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Active Vibration Suppression of Smart Cantilever Beam with Sliding Mode Observer Using Two Piezoelectric Patches
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This paper presents a vibration suppression control design of cantilever beam using two piezoelectric ‎patches. One patch was used as ‎an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. ‎the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state ‎estimation error is proved bounded. An ‎optimal LQR controller is designed then using the ‎estimated states with the slid

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Reality and constraints of the use of computers in public schools in the governorate of Ma'an From the standpoint of teachers
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 This study aims to recognize the process of using computer in    publicschools in Ma`an governorate in terms of hardware, capabilities, and teachers usage. It also aims to identify the most important obstacles those schools face from a teachers perspective.

            The study sample consists of (150) teachers from different disciplines. The researcher prepared two questionnaires related to the research pivotal, then presented to a group of arbitrators to be used in this final form. The data was analyzed statistically and the study concluded that there is a shortage in the computer services provided to teachers, and there is a w

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